The Advanced Metering Infrastructure (AMI), Distribution Automation

The main goal of this work is to propose a methodologyfor the implantation of solar roofs in the city of Nova Veneza, located in theState of Goiás (GO), and to carry out an economic feasibility study of theimplantation of photovoltaic systems, taking into account different scenarios,in the cities of Goiânia-GO and Nova-Veneza-GO.The demand for energy in the world has been increasingand along with this need, there is still growing concern about supplying thisdemand using renewable and sustainable sources. The Research & Development (R&D) Project No.

253of Celg Distribution (Celg-D) entitled “Application of Intelligent Network(Smart Grid) on the Supervision of Electricity Supply Medium and Low VoltageUsing Different Communication Technologies” was carried out between 2012 and2013 with the R&D program funds approved by the National Electric EnergyAgency (Aneel) 1. The project covers different areas of applications relatedto Smart Grids as Advanced Metering Infrastructure (AMI), DistributionAutomation (DA) and Integration of Celg-D systems. In addition, it wasdeveloped a consumer portal, opinion polls with consumers and a methodology forpositioning of concentrators in a Mesh Network (MN). Thus, the R&D projectNo. 253 allowed the Energy utility to have a direct contact with technologiesand systems for testing and technical evaluation in these areas 2.Fig.

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1 shows a simplified scheme for the installation ofmeters, with the need of hiring a GPRS data circuit (General Packet RadioService) to allow sending data collected from the meters for The SupervisionCenter, located in Goiânia-GO, based on the premises of Celg-D. Thus, meter dataare forwarded to a concentrator device as GPRS Data Connection that takesreadings directly to the energy utility 2. In thedevelopment of the R&D Project No.

253 the integration and the automationof the System of Service Orders and the measurement system was carried out byproposing that the service request is not created only by the CommercialBilling System (CBILL), but directly in the Technical System of OperationManagement (SGT-OPER). The process was based on information collected from themeters of Customer Consumer Units (CCU) and consolidated by the MeasurementCenter (MC). The advantage of this proposal is to eliminate the user’s need tonotify the Call Center, concentrating the interface between the MeasurementCenter and the SGT-OPER, thereby increasing the efficiency of the system 2.In the R Project No. 253, it was also proposed anapproach for positioning concentrators in a ZigBee Mesh Network (ZMN) of smartmeters in order to minimize the average delay of messages sent to the GPRS concentrators,resulting in a better network performance.

The K-means clustering algorithm isused to distribute the meters into subnetworks. Queuing Theory is used toestimate the average network delay and Binary Linear Programming (BLP) todetermine the location of the concentrators. In addition, computer simulationswere carried out to identify network performance from the position determinedby the proposed methodology 2. Other relevant work of the R Project No. 253were documented and published in 3 4 5 6 7.

The R Project No. 253 provided excellent resultsand expertise, leading us to propose the R Project No. 364 “51 Rooftopsin Nova Veneza-GO” 8.In order to verify the feasibility of Grid-ConnectedPhotovoltaic Systems in the city of Nova Veneza, state of Goiás (GO), it wasconducted a historical survey of the electricity consumption for consumersconnected to the TA and TB transformers shown in Fig. 1.

It is important to note the existence of a Smart MeteringSystem that monitors 123 consumers of Class B. There are 62 consumers beinglinked to the extension of low voltage transformer called TA, with nominalpower of 112.5 kVA, and 61 consumers linked to the extension of low voltagetransformer called TB with the same rating.

The Smart Metering System has the function of record andsend data on the energy consumption of Customer Consumer Units (CCU) for theMeasurement Center of Celg-D utility with the possibility to acknowledge powerfailure in certain three-phase consumer units. The system also checks thestatus of the difference between the power delivered in the secondary of thetransformer and the power actually consumed by the CCU, i.e., non-technicallosses.

Considering the historical survey of electricityconsumption for consumers connected to the TA and TB transformers, it wasproposed a methodology to choose 51 roofs in Nova Veneza-GO. The methodologyconsists of ten stages ranging from the grouping of consumers with the samepower consumption profile using a Neural Network (NN), that is, a NonParametric Self-Organizing Map (PSOM) 9, until the complete and optimalallocation of financial resources by an Integer Linear Programming (ILP).In the following sections will be presented themethodology for allocating the financial resources of the R Project No.364, as well as a grouping (clustering) proposal for the curves of consumptionprofiles of the consumer units of Nova Veneza-GO using Artificial NeuralNetworks. It will be also presented the traditional method used to project the Photovoltaic(PV) systems that will be connected to the grid of Nova Veneza-GO and asocioeconomic feasibility study for implementation of solar energy using Grid-TieSystems with and without financial incentive for all consumers of Group B ofNova Veneza-GO taking into account different values of PV Performance Rate.

Also shown in the following sections is a socioeconomic feasibility study forthe capital of Goiás, Goiânia. In this case, two scenarios were taken intoconsideration, with and without incentive for 5% and 30% of all consumers ofGroup B.


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